Various biological markers, known as biomarkers, have been identified and studied through the application of biochemistry and molecular biology to medical and toxicological situations. A biomarker has been described as “a characteristic that is objectively measured and evaluated as an indicator of normal biologic processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention”. A biomarker is any identifiable and measurable indicator associated with a particular condition or disease where there is a correlation between the presence or level of the biomarker and some aspect of the condition or disease (including the presence of, the level or changing level of, the type of, the stage of, the susceptibility to the condition or disease, or the responsiveness to a drug used for treating the condition or disease). The correlation may be qualitative, quantitative, or both qualitative and quantitative. Typically a biomarker is a compound, compound fragment or group of compounds. Such compounds may be any compounds found in or produced by an organism, including proteins (and peptides), nucleic acids and other compounds.
Biomarkers have a predictive power, and may be used to predict or detect the presence, level, type or stage of particular conditions or diseases (including the presence or level of particular microorganisms or toxins), the susceptibility (including genetic susceptibility) to particular conditions or diseases, or the response to particular treatments (including drug treatments). It is thought that biomarkers will play an increasingly important role in the future of drug discovery and development, by improving the efficiency of research and development programmes. Biomarkers can be used as diagnostic agents, monitors of disease progression, monitors of treatment and predictors of clinical outcome. For example, various biomarker research projects are attempting to identify markers of specific cancers and of specific cardiovascular and immunological diseases.
Proteomics (including peptidomics) technologies have been developed to analyse proteins (including peptides). These technologies are applied in a high-throughput mode, generating an enormous amount of data that is analysed using computer systems. Proteins from a biological sample are isolated and separated at a high resolution, for example by chromatographic separations. The set of proteins is then characterised using qualitative and quantitative techniques such as mass spectrometry. The result is a protein (or peptide) fingerprint (a constant, reproducible set of proteins or peptides). Selected proteins/peptides or groups of proteins/peptides may be analysed further to generate protein/peptide profiles. Proteomics is now viewed as the large-scale analysis of the function of genes and is becoming a central field in functional genomics.
Separation of proteins is commonly achieved using gel based techniques. 2D-PAGE (polyacrylamide gel electrophoresis) is currently the principal analytical method for studying the cellular expression of proteins. Instrumental platforms allow almost fully automated operations of 2D-gel analysis. The 2D-gel methods have good sensitivity and resolution for a large fraction of expressed proteins, typically those within a mass range of 10-120 kDa. However the methods have significant limitations in the identification of low abundance/low molecular weight proteins, some of which are present at concentrations as low as a few molecules per cell. Problems of sample loss and/or insufficient recovery have confounded the isolation of low abundance/low molecular weight proteins by 2D-PAGE. In addition, the presence of these proteins can be masked by the higher abundance protein spots. Other classes of proteins that are problematic for 2D-PAGE include acidic, basic, hydrophobic and high molecular weight proteins.
Multidimensional HPLC (High Performance Liquid Chromatography) has been used as a good alternative for separating proteins or peptides unsuited to 2D-PAGE. The protein or peptide mixture is passed through a succession of chromatographic stationary phases or dimensions which gives a higher resolving power. HPLC is also more flexible than the 2D-gel separation methods since the stationary and mobile phases can be selected for their suitability in resolving specific protein or peptide classes of interest and for compatibility with each other and with downstream mass spectrometric methods of detection and identification. On-line configurations of these types of multi-mechanism separation platforms are known.
Mass spectrometry (MS) is also an essential element of the proteomics field. In fact MS is the major tool used to study and characterise purified proteins in this field. The interface link in proteomics and MS, displaying hundreds or thousands of proteins, is made by gel technology where high resolution can be reached on a single gel. Researchers are successfully harnessing the power of MS to supersede the two-dimensional gels that originally gave proteomics its impetus.
The application and development of mass spectrometry (MS) to identify proteins or peptides separated via liquid phase separation techniques and/or gel-based separation techniques have led to significant technological advance in protein and peptide expression analysis. There are two main methods for the mass spectrometric characterization of proteins and peptides: matrix-assisted laser desorption ionization (MALDI) and electrospray ionization (ESI). Using various approaches, MALDI and ESI ion sources can be combined with time-of-flight (TOF) or other types of mass spectrometric analyzers to determine the masses or the sequences of peptides.
In MALDI, peptides are co-crystallized with the matrix, and pulsed with lasers. This treatment vaporizes and ionizes the peptides. The molecular weights (masses) of the charged peptides are then determined in a TOF analyzer. In this device, an electric field accelerates the charged molecules toward a detector, and the differences in the length of time it takes ionized peptides to reach the detector (their time-of-flight) reveal the molecular weights of the peptides; smaller peptides reach the detector more quickly. This method generates mass profiles of the peptide mixtures—that is, profiles of the molecular weights and amounts of peptides in the mixture. These profiles can then be used to identify known proteins from protein sequence databases.
In ESI and a technique called liquid chromatography (LC)/MS/MS, a voltage is applied to a very fine needle that contains a peptide mixture. The needle then sprays droplets into a mass spectrometric analyzer where the droplets evaporate and peptide ions are released. In LC/MS/MS, researchers use microcapilliary LC devices to initially separate peptides.
Mass spectrometry (MS) is a valuable analytical technique because it measures an intrinsic property of a bio-molecule, its mass, with very high sensitivity. MS can therefore be used to measure a wide range of molecule types (proteins, peptide, or any other bio-molecules) and a wide range of sample types/biological materials. Correct sample preparation is known to be crucial for the MS signal generation and spectra resolution and sensitivity. Sample preparation is therefore a crucial area for overall feasibility and sensitivity of analysis.
Proteins occur naturally within cells, as components of cellular structures and as components of natural biological fluids such as blood, urine, saliva, tears, lymph and sweat. Proteomics is an essential tool for studying biological systems and processes because proteins provide a rich source of valuable information. For example, this information allows the comparison of biomarkers that may differ qualitatively and/or quantitatively between healthy and diseased population groups. Proteomics technologies allow the identification of individual protein species in complex mixtures of proteins.
Proteomics are being used in drug discovery and development, for example to detect proteins significantly altered in patients with particular conditions or diseases. Some of these disease-associated proteins may be identified as novel drug targets and some may be useful as biomarkers of disease progression. Such biomarkers may be used to improve clinical development of a new drug or to develop new diagnostics for the particular disease.
Detection of disease-associated proteins may be achieved by the following method. Protein samples are taken from both diseased subjects and healthy subjects. These samples may be cells, tissues, or biological fluids that are processed to extract and enrich protein and/or peptide constituents. Typically the process entails partitioning into solution phase but may also include the establishment of protein and/or peptide components attached to solid matrixes. After high-throughput separation and analysis (proteomics), protein expression fingerprints are produced for either diseased or healthy subjects by qualitative and quantitative measurement. These fingerprints may be used as unique identifiers to distinguish individuals and/or establish and/or track certain natural or disease processes. These prototype fingerprints are established for each individual sample/subject and are recorded as numerical values in a computer database. The fingerprints are then analysed using bioinformatic tools to identify and select the proteins or peptides that are present in the prototype forms and whose expression may or may not be differentially present in the samples derived from the healthy and diseased subject samples. These proteins/peptides are then further characterised and detailed profiles are produced which identify the characteristic masses and physical properties of the proteins or peptides. Either a singular proteins/peptide or groups of proteins/peptides may be determined to be significantly associated with certain natural or diseased processes.
Various disease-associated proteins are known, and some of these are enzymes whose activity increases or decreases at some stage in the development of a particular condition or disease. Such enzymes may be suitable drug targets, leading to a search for pharmaceutically-active compounds (drugs) that could be used to inhibit or stimulate the enzyme and thus prevent or treat the condition or disease. Other disease-associated proteins may be degradation products of particular enzymes, or proteins that are made more abundantly in the presence of the disease.
Examples of disease-associated proteins include the metalloproteinases, a superfamily of proteinases (enzymes) believed to be important in a plethora of physiological disease processes. Modulation of the activity of one or more metalloproteinases may well be of benefit in these diseases or conditions. A number of metalloproteinase inhibitors are known (see for example the reviews of MMP inhibitors by Beckett R. P. and Whittaker M., 1998, Exp. Opin. Ther. Patents, 8(3):259-282, and by Whittaker M. et al, 1999, Chemical Reviews 29(9):2735-2776). Based on structural and functional considerations metalloproteinase enzymes have been classified into families and subfamilies as described in N. M. Hooper (1994) FEBS Letters 354:1-6. Examples of metalloproteinases include the matrix metalloproteinases (MMPs) such as the collagenases (MMP1, MMP8, MMP13), the gelatinases (MMP2, MMP9), the stromelysins (MMP3, MMP10, MMP11), matrilysin (MMP7), metalloelastase (MMP12), enamelysin (MMP19), and the MT-MMPs (MMP14, MMP15, MMP16, MMP17).
Examples of disease-associated proteins include those enzymes that have been implicated in the onset and/or progression of Chronic Obstructive Pulmonary Disease (COPD), as discussed below.
COPD, which is mainly caused by cigarette smoking, is expected to be the third leading cause of death worldwide by the year 2020. COPD is characterised by reduced maximum expiratory flow and slow forced emptying of the lungs. These airflow limitations are mainly due to chronic bronchitis, involving hypertrophy of mucous glands, and emphysema produced by destruction of alveolar walls. The latter leads to enlargement of the air spaces distal to the terminal bronchiole, with consequent collapse of small airways, limitations of the airflow, destruction of parts of the capillary bed, and loss of the elastic recoil of the lung. This loss of elastic recoil and the enlargement of the air spaces in the lungs of COPD patients lead to reduced values of forced expiratory volume (FEV), and increased values of forced vital capacity (FVC). Disease severity is determined as the degree of lung function impairment, which is measured with a spirometer. The presence of a postbronchodilator FEV1<80% of the predicted value in combination with an FEV1/FVC<70% confirms the presence of airflow limitation that is not fully reversible. The chronic exposure to cigarette smoke causes an inflammatory response in the lung, leading to changes in the airway epithelial surface and to activation and an increased number of several inflammatory cells.
Inflammation and a protease-antiprotease imbalance have long been proposed to act as downstream effectors of the lung destruction following chronic cigarette smoking. Histological studies have demonstrated increased numbers of macrophages and T-lymphocytes in the airways of smokers, and also an increase of neutrophils in the airways of smokers and COPD patients, which related to the severity of the airway obstruction. Alveolar macrophages are long-lived phagocytes, and are the most abundant defence cells in the lung both under normal conditions and during chronic inflammation. By sending out chemotactic factors they then recruit neutrophils and lymphocytes by activating adhesion molecule expression on pulmonary microvascular endothelial cells at the site of infection. The inflammatory cells invading the smoker's lung produce mediators locally, such as cytokines, serine- and metalloproteases, and oxidants. These mediators, which likely play an important role in the development of COPD, can act to further activate the inflammatory response, and also to degrade the components of the extracellular matrix.
Normally plasma proteinase inhibitors, especially α1-antitrypsin (α1-AT), prevent proteolytic enzymes from digesting structural proteins of the lung. According to the proteinase-antiproteinase hypothesis, emphysema result from an increase of proteinase release in the lungs, a reduction in the antiproteinase defense, or a combination. Elastin is the principal component of elastic fibres constituting a main part of the lung's extracellular matrix. Studies show that individuals who are homozygous for α1-AT deficiency have an increased susceptibility for developing pulmonary emphysema, especially if they also smoke.
One example of a disease-associated enzyme linked to COPD is the matrix metalloproteinase MMP12, also known as macrophage elastase or metalloelastase. One of MMP12's natural substrates is elastin, the insoluble, elastic protein of high tensile strength found in intercellular spaces of the connective tissues of large arteries, trachea, bronchi and ligaments. MMP12 was initially cloned in the mouse by Shapiro et al [1992, Journal of Biological Chemistry 267: 4664] and then in man by the same group (Shapiro et al, “Cloning and characterization of a unique elastolytic metalloproteinase produced by human alveolar macrophages”, 1993, Journal of Biological Chemistry 268 (32): 23824-23829). The protein sequence of a human MMP12 is stored in the SwissProt database available at http://us.expasy.org/sprot/(swissprot: locus MM12_HUMAN, accession P39900). MMP-12 is preferentially expressed in activated macrophages, and has been shown to be secreted from alveolar macrophages from smokers [Shapiro et al, 1993, Journal of Biological Chemistry, 268: 23824-23829] as well as in foam cells in atherosclerotic lesions [Matsumoto et al, 1998, Am J Pathol 153: 109]. A mouse model of chronic obstructive lung disease (COPD) is based on challenge of mice with cigarette smoke for six months, two cigarettes a day six days a week. Wildtype mice developed pulmonary emphysema after this treatment. When MMP12 knock-out mice were tested in this model they developed no significant emphysema, strongly indicating that MMP-12 is a key enzyme in the COPD pathogenesis. MMP12 is believed to degrade lung tissue by degrading the elastin within the tissue. The role of MMPs such as MMP12 in COPD (emphysema and bronchitis) is discussed in Anderson and Shinagawa, 1999, Current Opinion in Anti-inflammatory and Immunomodulatory Investigational Drugs 1(1): 29-38. It was recently discovered that smoking increases macrophage infiltration and macrophage-derived MMP-12 expression in human carotid artery plaques Kangavari [Matetzky S, Fishbein M C et al., Circulation 102:(18), 36-39 Suppl. S, Oct. 31, 2000].
The current use of proteomics or peptidomics in drug discovery and development (particularly for the disease COPD) is limited by various factors, including for example:                a) the lack of profiles of disease-associated peptides that can be linked to specific drug targets (because current fingerprinting methods analyse total protein differences, and do not focus on a particular protein/drug target);        b) the lack of biomarkers to identify COPD sufferers at an early stage of the disease;        c) the lack of biomarkers to evaluate potential drugs that are MMP12 inhibitor compounds, particularly in clinical studies (ie for validation that the MMP12 target is hit by the inhibitor).        